Multiscale directional filtering of noisy InSAR phase images

Vishal M. Patel, Glenn R. Easley, Rama Chellappa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this work, we present a new approach for the problem of interferometric phase noise reduction in synthetic aperture radar interferometry based on the shearlet representation. Shearlets provide a multidirectional and multiscale decomposition that have advantages when dealing with noisy phase fringes over standard filtering methods. Using a shearlet decomposition of a noisy phase image, we can adaptively estimate a phase representation in a multiscale and anisotropic fashion. Such denoised phase interferograms can be used to provide much better digital elevation maps (DEM). Experiments show that this method performs significantly better than many competitive methods.

Original languageEnglish (US)
Title of host publicationIndependent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII
DOIs
StatePublished - 2010
EventIndependent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII - Orlando, FL, United States
Duration: Apr 7 2010Apr 9 2010

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7703

Other

OtherIndependent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII
Country/TerritoryUnited States
CityOrlando, FL
Period4/7/104/9/10

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Applied Mathematics
  • Electrical and Electronic Engineering
  • Computer Science Applications

Keywords

  • Coherence
  • Phase Denoising
  • SAR
  • SAR Interferometry
  • Shearlets
  • Wavelets

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